Computing systems, such as data transaction processing systems, often process data objects which are associated with values derived from or otherwise submitted or provided by external sources. Incoming messages related to the data objects may include requests for transactions which are triggered by, or otherwise perform actions on, the data objects at specified values. Whether or not the attempted actions are executed or performed depend in part on the values submitted with the incoming messages and/or the rules and processing routines programmed into a data transaction processing system.
One example of an environment including data objects having specified values is an electronic trading system wherein the values may be submitted by participants, e.g. traders. Electronic trading systems include objects having values associated therewith. Object values may change over time, and some changes to the value of an object may be undesirable or based on incomplete or inaccurate data. Some integrity systems prevent undesirable changes in values over time or undesirable gaps between reference and received or incoming values.
However, such integrity systems add additional processing overhead, increasing the overall processing times and overall latency of a data transaction processing system. Modern data transaction processing systems process thousands, hundreds of thousands, or even millions of messages per day. Routing each message through integrity systems can create a bottleneck, creating latency and adversely affecting processing speeds.